TWIMLfest 2020


Photo: Claire Monteleoni

Claire Monteleoni

Associate Professor
University of Colorado Boulder
Connect with Claire

Professor Claire Monteleoni's Machine Learning Group is concerned with developing principled methods (known as algorithms) to automatically detect patterns in data. In this era of "Big Data," the various forms of complexity inherent in real data sources increasingly pose challenges for machine learning algorithm design. The GW Machine Learning Group works on the design, analysis, and application of machine learning algorithms, motivated by problems in real data sources, including learning from data streams, learning from raw (unlabeled) data, learning from private data, and climate informatics: accelerating discovery in climate science with machine learning.

Conference Sessions

AI and Society
TWIMLfest  2020
This panel will focus on the latest developments in the fight to slow climate change with an emphasis on the application of AI and ML, the implications of energy policy on deep learning and how GANs can help visualize climate change and it's impact, as well as high impact opportunities to get involved.